Software Engineer, AI Pod

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

AI Pod is Toast's internal platform team for AI. We build the infrastructure, governance, and developer tooling that makes AI a reliable, scalable force multiplier across the entire product development lifecycle. Our products include the LLM Proxy, AI Key Management, Observability pipelines, the Claude Plugin Marketplace, and autonomous agents that participate directly in the software development lifecycle.

As a Staff Software Engineer on this team, you'll shape the foundation others build on: from the LLM Proxy that routes all internal AI traffic, to autonomous agents that participate directly in the software development lifecycle. If you want to work at the frontier of AI infrastructure and see your work amplify hundreds of engineers across a fast-growing company, this is the role.

• Design, build, and ship core AI platform infrastructure, including the LLM proxy, AI key management, and observability pipelines powering Toast's internal AI ecosystem
• Architect and deliver autonomous agents that participate in the SDLC, including the AI Review Git Hub App and Developer Platform MCP integrations
• Build on and help maintain the internal plugin marketplace, developing plugins that encode Toast's architectural standards, PR patterns, and quality practices directly into AI assistant behavior
• Lead technical design and implementation of MCP (Model Context Protocol) services and no-code service templates that accelerate AI-powered development across Toast
• Mandated self‑not ???
• Mandated self‑not???
• Mandated self‑not???

• 8+ years of experience designing and implementing scalable backend services
• Strong foundation in Java, Kotlin, or another object-oriented language, with experience building scalable backend services
• Demonstrated experience building, deploying, or operating LLM-powered agents or AI-assisted developer tooling
• Deep familiarity with AI coding assistants (e.g., Claude Code, Cursor, Git Hub Copilot) and the ability to extend them through custom plugins, skills, or hooks
• Hands‑on experience with MCP (Model Context Protocol), tool use patterns, or agentic frameworks
• Strong prompt engineering skills and intuition for how LLM behavior changes with context, instructions, and tool definitions